For track maintenance, there are primarily three generic sensor data fusion algorithm architectures, namely, central fusion, track fusion, and what will be referred to as composite measurement fusion. In central fusion, the sensor measurements are distributed by each sensor and the measurements from multiple sensors are then used to update the global tracks. Measurements are also called: returns, observations, threshold exceedances, plots, contacts, or hits depending on the sensors involved. In contrast, in track fusion a sequence of measurements is processed at the sensor or platform level to form tracks that are then distributed and this track data is then used to update the global tracks. Track fusion is also sometimes called hierarchical fusion, federated fusion or distributed fusion. Finally, in composite measurement fusion the measurements from multiple sensors for each apparent target are first combined to form a composite measurement and then the composite measurements are then used to update the global tracks. The tracks typically include features or other target classification information. Each of these algorithm architectures has their own advantages and disadvantages. For example, track fusion may lead to substantially reduced communications load and that can be important for physically distributed platforms. Track fusion also tends to be less sensitive to residual sensor bias errors. Central fusion typically provides more timely information. Also, for certain types of target scenarios and sensor suites, central fusion provides better accuracy in both estimation and target classification. Recent developments in track fusion make a particular hybrid fusion algorithm architecture not only appealing but practical. In this hybrid fusion, either measurement or track data in the form of a tracklet is distributed from a sensor for a target. This approach offers many of the advantages of both the centralized and track fusion algorithm architectures. This paper describes a specific hybrid fusion algorithm architecture, the decision logic for distributing measurement or track data, and the recent track fusion innovations that make this hybrid fusion practical.